{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "18f12879",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a429304c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array([[51,55],[14,19],[0,4]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6bba0a9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[51, 55],\n",
       "       [14, 19],\n",
       "       [ 0,  4]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "87a0d8f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([51, 55, 14, 19,  0,  4])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a4c28c6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = X.flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8bcff850",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([51, 14,  0])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y[np.array([0,2,4])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c9456f5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ True,  True],\n",
       "       [False,  True],\n",
       "       [False, False]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X > 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "898d0541",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True, False,  True, False, False])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y > 15"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b8efccf",
   "metadata": {},
   "source": [
    "对NumPy数组使用不等号运算符等（上例中是 X > 15） ,结果会得到一个\n",
    "布尔型的数组。下面的例子就是使用这个布尔型数组取出了数组的各个元素（取\n",
    "出True对应的元素）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a48cb88f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([51, 55, 19])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y[Y>15]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f36ac29",
   "metadata": {},
   "source": [
    "# Matplotlib使用"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f533d232",
   "metadata": {},
   "source": [
    "## 绘制线条"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2f8e6623",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0815632a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0, 6, 0.1)\n",
    "y1 = np.sin(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c2239bef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "28cc92e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "y2 = np.cos(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "57324349",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y1, label='sin')\n",
    "plt.plot(x, y2, linestyle='--', label='cos')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.title('sin & cos')\n",
    "plt.legend()\n",
    "# plt.show()\n",
    "plt.savefig('sin.png', transparent=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cf5f5a6",
   "metadata": {},
   "source": [
    "matplotlib绘图教程: https://stackabuse.com/save-plot-as-image-with-matplotlib/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6a8e6e33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "# 改变绘图的颜色\n",
    "plt.rcParams[\"figure.facecolor\"] = 'red'\n",
    "\n",
    "x = np.arange(0, 10, 0.1)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.savefig('saved_figure-colored.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4c1e367",
   "metadata": {},
   "source": [
    "## 显示图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2b12b144",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.image import imread"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d62a16b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = imread('sin.png')\n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09d21701",
   "metadata": {},
   "source": [
    "# 推荐学习资料\n",
    "\n",
    "  - python基础编程：《[python语言及其应用](https://book.douban.com/subject/26675127/)》\n",
    "  - numpy学习: 《[利用python进行数据分析]()》\n",
    "  - 学习numpy和matplotlib的网站：Scipy Lecture Notes"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
